Short-term fire forecast based on air state gain recurrence and zero-order brown model

Authors

DOI:

https://doi.org/10.15587/1729-4061.2021.233606

Keywords:

fire forecasting, zero-order Brown model, out-of-limit set, ignition, recurrence measure

Abstract

Possibilities of parameterization of the zero-order Brown model for indoor air forecasting based on the current measure of air state gain recurrence are considered. The key to the zero-order parametric Brown forecasting model is the selection of the smoothing parameter, which characterizes forecast adaptability to the current air state gain recurrence measure. It is shown that for effective short-term indoor fire forecast, the Brown model parameter must be selected from the out-of-limit set defined by 1 and 2. The out-of-limit set for the Brown model parameter is an area of effective fire forecasting based on the measure of current indoor air state gain recurrence. Errors of fire forecast based on the parameterized zero-order Brown model in the case of the classical and out-of-limit sets of the model parameters are investigated using the example of ignition of various materials in a laboratory chamber. As quantitative indicators of forecast quality, the absolute and mean forecast errors exponentially smoothed with a parameter of 0.4 are investigated. It was found that for alcohol, the smoothed absolute and mean forecast errors for the classical smoothing parameter in the no-ignition interval do not exceed 20 %. At the same time, for the out-of-limit case, the indicated forecast errors are, on average, an order of magnitude smaller. Similar ratios for forecast errors remain in paper, wood and textile ignition. However, for the transition zone corresponding to the time of material ignition, a sharp decrease in the current measure of chamber air state gain recurrence is observed. It was found that for this zone, the smoothed absolute forecast error for alcohol is about 2 % if the model parameter is selected from the classical set. If the model parameter is selected from the out-of-limit set, the forecast error is about 0.2 %. The results generally demonstrate significant advantages of using the zero-order Brown parametric model with out-of-limit model parameters for indoor fire forecasting

Author Biographies

Boris Pospelov, Scientific-methodical Center of Educational Institutions in Sphere of Civil Defence

Doctor of Technical Sciences, Professor

Department of Organization and Coordination of Research Activities

Evgenіy Rybka, National University of Civil Defence of Ukraine

Doctor of Technical Sciences, Senior Researcher

Research Center

 

Ruslan Meleshchenko, National University of Civil Defence of Ukraine

PhD, Associate Professor

Department of Fire and Rescue Training

Olekcii Krainiukov, V. N. Karazin Kharkov National University

Doctor of Geographical Sciences, Associate Professor

Department of Environmental Safety and Environmental Education

Igor Biryukov, National Academy of National Guard of Ukraine

Doctor of Technical Sciences, Associate Professor

Department of Missile and Artillery Weapons

Tetiana Butenko, Scientific-methodical Center of Educational Institutions in Sphere of Civil Defence

PhD, Senior Research

Department of Organization and Coordination of Research Activities

Oleksandr Yashchenko, National University of Civil Defence of Ukraine

PhD, Associate Professor

Department of Management and Organization of civil Defence

Yuliia Bezuhla, National University of Civil Defence of Ukraine

PhD, Associate Professor

Department of Prevention Activities and Monitoring

Kostiantyn Karpets, V. N. Karazin Kharkov National University

PhD, Associate Professor

Department of Ecology and Neoecology

Ruslan Vasylchenko, National Academy of National Guard of Ukraine

PhD

Department of Research and Organization

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Published

2021-06-30

How to Cite

Pospelov, B., Rybka, E., Meleshchenko, R., Krainiukov, O., Biryukov, I., Butenko, T., Yashchenko, O., Bezuhla, Y., Karpets, K., & Vasylchenko, R. (2021). Short-term fire forecast based on air state gain recurrence and zero-order brown model. Eastern-European Journal of Enterprise Technologies, 3(10(111), 27–33. https://doi.org/10.15587/1729-4061.2021.233606

Issue

Vol. 3 No. 10(111) (2021): Ecology

Section

Ecology

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Copyright (c) 2021 Boris Pospelov, Evgenіy Rybka, Ruslan Meleshchenko, Olekcii Krainiukov, Igor Biryukov, Tetiana Butenko, Oleksandr Yashchenko, Yuliia Bezuhla, Kostiantyn Karpets, Ruslan Vasylchenko

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